摘要
随着大数据技术的发展和移动终端设备的普及,大量轨迹数据得以被采集并存储到互联网上。现今较易获得的轨迹数据使其越来越受到研究者的关注,由于这些原始的轨迹数据受到采样频率、采样精度以及法律法规的影响,而通常不能直接应用到各类挖掘算法中,因此通常需要先进行预处理。该文对轨迹数据的预处理进行了综述。首先,介绍了轨迹数据的概念和用途;其次,总结了轨迹数据的常见特征;再次,归纳了常用的轨迹数据预处理方式;最后,论述了轨迹数据处理面临的挑战并对未来研究方法进行了展望。
With the development of big data technology and the popularization of mobile terminal devices,a large amount of trajectory data can be collected and uploaded to the internet.In recent years,more and more scholars pay attention to the trajectory data easy to be obtained.These original trajectory data affected by sampling frequency,sampling accuracy and laws and regulations,can not be directly applied to various mining algorithms,so,pretreatment is usually needed first.This paper reviews trajectory data pretreatment.Firstly,the concept and application of trajectory data are introduced.Secondly,the common characteristics of trajectory data are summarized.Thirdly,the common track data pretreatment methods are summarized.Finally,the challenges of trajectory data pretreatment are discussed and the future research methods are prospected.
作者
蔡郑
贾利娟
孙扬清
CAI Zheng;JIA Li-juan;SUN Yang-qing(Nanjing Vocational University of Industry Technology,Nanjing 210046,China)
出处
《电脑知识与技术》
2020年第31期9-12,共4页
Computer Knowledge and Technology
基金
南京工业职业技术学院科研基金项目(YK17-12-03)。
